A review on substances and processes relevant for optical remote sensing of extremely turbid marine areas, with a focus on the Wadden Sea

The interpretation of optical remote sensing data of estuaries and tidal flat areas is hampered by optical complexity and often extreme turbidity. Extremely high concentrations of suspended matter, chlorophyll and dissolved organic matter, local differences, seasonal and tidal variations and resuspension are important factors influencing the optical properties in such areas. This review gives an overview of the processes in estuaries and tidal flat areas and the implications of these for remote sensing in such areas, using the Wadden Sea as a case study area. Results show that remote sensing research in extremely turbid estuaries and tidal areas is possible. However, this requires sensors with a large ground resolution, algorithms tuned for high concentrations of various substances and the local specific optical properties of these substances, a simultaneous detection of water colour and land-water boundaries, a very short time lag between acquisition of remote sensing and in situ data used for validation and sufficient geophysical and ecological knowledge of the area. © 2010 The Author(s)

Modelling the effect of temperature and water activity of Aspergillus flavus isolates from corn

The aim of this study was to model the effects of temperature (10–40 °C) and aw (0.80–0.98), in two media (Czapek yeast agar: CYA; corn extract medium: CEM) on the growth rates and growth boundaries (growth–no growth interface) of three strains of A. flavus isolated from corn in Argentina. Both kinetic and probability models were applied to colony growth data. The growth rates obtained in CYA were significantly (p < 0.05) greater than those obtained in CEM medium. No significant differences (p < 0.05) were observed among the three isolates. The growth rate data showed a good fit to the Rosso cardinal models combined with the gamma-concept with R2 = 0.98–0.99 and RMSE = 0.60–0.78, depending on media and isolates. The probability model allowed prediction of safe storage (p of growth < 0.01) for one month for moist maize (e.g. 0.90 aw) provided temperature is under 15 °C, or for dry maize (e.g. 0.80 aw) provided temperature is under 27 °C. Storage at < 0.77 aw would be safe regardless of the storage temperature. Probability models allow evaluation of the risk of fungal contamination in the process of storage, so the results obtained in this study may be useful for application in systems of food safety management.Fil: Astoreca, Andrea Luciana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Orgánica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Investigación y Desarrollo En Fermentaciones Industriales. Universidad Nacional de la Plata. Facultad de Cs.exactas. Centro de Investigación y Desarrollo En Fermentaciones Industriales; ArgentinaFil: Vaamonde, Graciela. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Orgánica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Micología y Botánica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Micología y Botánica; ArgentinaFil: Dalcero, Ana Maria. Universidad Nacional de Rio Cuarto. Facultad de Ciencias Exactas Fisicoquimicas y Naturales; ArgentinaFil: Ramos, A. J.. Universidad de Lleida; EspañaFil: Marin, S.. Universidad de Lleida; Españ

Comparative study of analytical techniques for deoxynivalenol detection and quantification in wheat samples destined for the manufacture of commercial products

The concern regarding toxicity from the presence of deoxynivalenol (DON) in wheat that affects both economy and public health leads to the need to find appropriate detection methods for determining the degree of DON contamination in terms of the equipment available and the speed required for obtaining the incidence. The objective of this study was to compare the performance of two alternative analytical techniques for DON quantification for use in the food industry with a reference technique. Samples of wheat and the commercial by-products were analysed by high-performance liquid chromatography (HPLC) with an ultraviolet detector as the reference method and the results compared with those obtained from a rapid lateral-flow immunochromatographic device (Reveal Q+) and of a Fourier-transform-infrared (FTIR) spectroscopy technique. Pearson?s correlation coefficient between the HPLC and Reveal-Q+ data (0.45), although significant (P<0.0003), was lower than that obtained between HPLC and the FTIR method (0.94, P<0.0001). Both methods were considered efficient in quantifying DON levels in wheat-flour samples. This study was aimed at assisting the producers in choosing an appropriate tool for the purpose of analysis and upon consideration of the available equipment.Fil: Astoreca, Andrea Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Fermentaciones Industriales. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Fermentaciones Industriales; ArgentinaFil: Ortega, Leonel Maximilano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Fermentaciones Industriales. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Fermentaciones Industriales; ArgentinaFil: Fígoli, Cecilia Beatríz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Fermentaciones Industriales. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Fermentaciones Industriales; ArgentinaFil: Cardós, M.. Molino Campodonico; ArgentinaFil: Cavaglieri, Lilia Reneé. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales. Departamento de Microbiología e Inmunología; ArgentinaFil: Bosch, A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Fermentaciones Industriales. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Fermentaciones Industriales; ArgentinaFil: Alconada Magliano, Teresa Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Fermentaciones Industriales. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Fermentaciones Industriales; Argentin